Staff Data Scientist, Actuarial at Nourish in New York, NY
- Company: Nourish
- Location: New York, NY
- Job type: full time
- Workplace: onsite
- Posted: 2026-10-29
Job description
About Us Health is the most important thing in life, and the American healthcare system is completely broken - poor outcomes, high cost, bad patient experience. We're building a new system from the ground up. Our mission is to improve people’s health by making it easy to live a healthy lifestyle. Nourish is the country's largest dietitian-led metabolic health clinic. We’re an AI-native digital health system matching patients with 10,000+ Registered Dietitians, physicians, medications, lab testing, and AI agents to deliver insurance-covered care across all 50 states. Founded four years ago, we've completed millions of appointments, tripled year-over-year, and partnered with health plans covering 200M+ Americans across 250+ health systems. In 2026 we raised a $100M Series C , bringing total funding to $215M. The round was led by Menlo Ventures , with participation from Thrive Capital , Index Ventures , J.P. Morgan Growth Equity Partners , Maverick Ventures , Y Combinator , BoxGroup , Atomico , Daybreak , and Operator Partners . Learn more about our Series C here: Nourish Blog , Bloomberg , Fierce Healthcare , Digital Native , The Pulse Podcast . This is not a job for everyone. We hold an extremely high bar because we believe talent density is our biggest competitive advantage. We're looking for people who actively choose hard, ambiguous problems, who run toward unglamorous work, give and receive candid feedback, and bring relentless resilience without the ego. Our work is important, but we are not self-important. We do this because we’re solving one of the hardest problems in the world, and the problem matters. If that's you, we disproportionately reward it. About the Role Can nutrition care meaningfully improve health outcomes while reducing healthcare costs? This question is critical to Nourish's mission and our ability to bring care to millions more patients. As our Actuarial Data Scientist , you'll lead the effort to quantify the economic impact of Nourish care. You'll design rigorous claims-based studies, develop actuarial models, and translate your findings into compelling evidence that demonstrates the value of Nourish to existing and prospective payer partners. You'll be our first dedicated actuarial data science hire, with the opportunity to shape how we measure, validate, and communicate our impact. Your work will directly influence our payer partnerships, commercial strategy, and understanding of where our care creates the most value. This is a hands-on role, working closely with our Commercial and Clinical teams, partnering with Analytics Engineering, and reporting to our Head of Data. Our data team is based in NYC and works from the office 3+ days a week, so we're looking for people who are excited to join us onsite and be part of that culture. Key Responsibilities Lead Nourish's payer value studies: Design and execute rigorous claims-based analyses to quantify the impact of Nourish care on medical and pharmacy spending, healthcare utilization, and total cost of care. Develop credible causal impact estimates: Apply appropriate study designs, matched comparison groups, risk adjustment, and causal inference methods to isolate the incremental impact of Nourish care. Model financial impact for prospective partners: Build actuarial models to estimate potential cost savings, PMPM impact, and ROI for specific health plan populations. Translate evidence into compelling narratives: Produce clear study reports and executive summaries for health plan partners. Work alongside our Commercial team to communicate findings, explain methodologies and limitations, and address actuarial and clinical questions. Identify where Nourish generates the greatest savings: Analyze which patient populations, conditions, and healthcare cost drivers offer the greatest potential for savings, and translate findings into actionable recommendations for our Commercial and Clinical teams. Build a scalable analytical foundation: Partner with Analytics E
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